CN114971412A - Order distribution method, order distribution platform, order distribution system and storage medium - Google Patents
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Abstract
The invention discloses an order distribution method, an order distribution platform, an order distribution system and a storage medium, wherein the method comprises the following steps: receiving order information uploaded by a user through a terminal, wherein the order information comprises user grade and reservation address information; the method comprises the steps of obtaining grade information of all operators, and screening out a first operator set with the grade information matched with a user grade; acquiring real-time position information of each salesman in a first salesman set, and screening a second salesman set with the real-time position information matched with the reservation address information from the first salesman set; all the salesmen in the second salesmen set are subjected to priority sequencing based on a preset rule; and distributing the order information to a task list of a target operator, wherein the target operator is the operator with the highest priority order so as to ensure that the order can be processed in time. The order distribution scheme increases the diversity of order distribution modes, and has high flexibility and good user experience.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to an order allocation method, an order allocation platform, an order allocation system, and a storage medium.
Background
With the development of computer technology, various financial services of banks, such as account opening, account transfer, credit card transaction, financial transaction and the like, can be transacted through a computer. When a banking clerk needs to transact business at home, the current business order distribution mode is usually to send the order to the clerk whose real-time location information is consistent with the order reservation address information. When the number of orders of the service staff with the real-time location information consistent with the order reservation address information is large, if a plurality of newly received orders are also given to the service staff for processing, the service staff may not process the orders, which will affect the processing speed of the orders. Therefore, the existing order distribution mode is too single and not flexible.
Disclosure of Invention
The present application aims to provide an order allocation method, an order allocation platform, an order allocation system and a storage medium, so as to solve the problem that the order allocation method in the prior art is too single and not flexible enough.
A first aspect of an embodiment of the present application provides an order allocation method, including:
receiving order information uploaded by a user through a terminal, wherein the order information comprises user grade and reservation address information;
grade information of all the salesmen is obtained, and a first salesmen set with the grade information matched with the user grade is screened out;
acquiring real-time position information of each salesman in a first salesman set, and screening out a second salesman set with the real-time position information matched with the reservation address information from the first salesman set;
all the salesmen in the second salesmen set are subjected to priority sequencing based on a preset rule;
and distributing the order information to a task list of a target operator, wherein the target operator is the operator with the highest priority order.
In an embodiment, the obtaining of the grade information of all the operators includes:
acquiring service information of a waiter;
and determining a corresponding service type according to the service information, inputting the service type into a preset salesman matching model for matching, and obtaining grade information matched with the service information.
In one embodiment, the screening out the second salesman set from the first salesman set that the real-time location information matches with the reservation address information includes:
carrying out gridding division on the urban area according to population density distribution to obtain a plurality of grid areas;
and taking the grid area where the reservation address information is located as a center, and if the real-time position information is located in 8 grid areas surrounding the center, matching the real-time position information with the reservation address information, wherein the central grid area and the 8 grid areas surrounding the center are distributed according to a Sudoku.
In one embodiment, the screening out the second salesman set from the first salesman set that the real-time location information matches with the reservation address information includes:
drawing a thermodynamic diagram according to historical order position information of a target city area;
carrying out gridding division on the thermodynamic diagram according to a preset proportion strategy to obtain a plurality of grid areas;
and taking the grid area where the reservation address information is located as a center, and if the real-time position information is located in 8 grid areas surrounding the center, matching the real-time position information with the reservation address information, wherein the central grid area and the 8 grid areas surrounding the center are distributed according to a Sudoku.
In one embodiment, the screening out the second salesman set from the first salesman set that the real-time location information matches with the reservation address information includes:
and if the path distance between the real-time position information and the reservation address information is smaller than or equal to a preset distance, matching the real-time position information with the reservation address information.
In one embodiment, the prioritizing all the employees in the second set of employees based on a preset rule includes,
all the service data in the latest preset time range are obtained regularly, the obtained service data are input into a preset data statistical analysis system for statistical analysis, and the numerical values of all the preset performance indexes of each salesman are obtained through statistical analysis;
calculating the obtained numerical value of each preset performance index of each salesman according to a preset score calculation rule to obtain the total performance score of each salesman;
and the various salesmen are prioritized according to the total performance score from high to low.
A second aspect of an embodiment of the present application provides an order distribution platform, including:
the receiving module is used for receiving order information uploaded by a user through a terminal, and the order information comprises user grade and reservation address information;
the first screening module is used for acquiring the grade information of all the salesmen and screening out a first salesmen set of which the grade information is matched with the user grade;
the second screening module is used for acquiring real-time position information of each salesman in the first salesman set and screening out a second salesman set with the real-time position information matched with the reservation address information from the first salesman set;
the priority ordering module is used for carrying out priority ordering on all the salesmen in the second salesmen set based on a preset rule;
and the distribution module is used for distributing the order information to a task list of a target operator, wherein the target operator is the operator with the highest priority order.
A second aspect of an embodiment of the present application provides an order distribution platform, including:
the receiving module is used for receiving a plurality of order information uploaded by a plurality of users through terminals, wherein the order information comprises reservation address information;
the region determining module is used for determining a target region and an adjacent region according to the reservation address information and a preset region division rule;
the determining module is used for acquiring real-time position information corresponding to each salesman, and determining a first salesman list of which the real-time position information is located in the target area and a second salesman list of which the real-time position information is located in the adjacent area;
the acquisition module is used for acquiring the current unfinished order number of each salesman in the first salesman list;
the judging module is used for judging whether the current unfinished order quantity of all the salesmen in the first salesmen list is larger than a preset unfinished order quantity;
and the distribution module is used for distributing a plurality of order information to a task list of a target operator when the current number of unfinished orders of all operators in the first operator list is greater than the preset number of unfinished orders, wherein the target operator is a plurality of operators of which the current number of unfinished orders in the second operator list is less than the preset number of unfinished orders.
A third aspect of the embodiments of the present application provides an order allocation platform, which includes a memory, a processor, and a computer program stored in the memory and executable on a computer device, where the processor implements the steps of the order allocation method provided by the first scheme when executing the computer program.
A fourth aspect of the embodiments of the present application provides an order distribution system, which includes a plurality of clients, a server, and the order distribution platform as described above; and the plurality of clients and the server are in communication connection with the platform.
A fifth aspect of embodiments of the present application provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the steps of the order allocation method provided by the first aspect.
The order distribution method, the order distribution platform, the order distribution system and the storage medium provided by the embodiment of the application have the following beneficial effects:
according to the order distribution method, the order distribution platform, the order distribution system and the storage medium, the order information uploaded by a user through a terminal is received, and the order information comprises user grade and reservation address information; acquiring grade information of all the operators, and screening out a first operator set with the grade information matched with the user grade; acquiring real-time position information of each salesman in a first salesman set, and screening out a second salesman set with the real-time position information matched with the reservation address information from the first salesman set; all the salesmen in the second salesmen set are subjected to priority sequencing based on a preset rule; and distributing the order information to a task list of a target operator, wherein the target operator is the operator with the highest priority order so as to ensure that the order can be processed in time. The order distribution scheme increases the diversity of order distribution modes, and has high flexibility and good user experience.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
FIG. 1 is a flow chart of a first implementation of an order allocation method according to an embodiment of the present invention;
FIG. 2 is a flowchart of a second implementation of an order allocation method according to an embodiment of the present invention;
FIG. 3 is a flowchart of a third implementation of an order allocation method according to an embodiment of the present invention;
FIG. 4 is a first flowchart of step S20 in FIG. 1;
FIG. 5 is a second flowchart of step S20 in FIG. 1;
FIG. 6 is a functional block diagram of an order distribution platform according to an embodiment of the present invention;
fig. 7 is a schematic hardware structure diagram of an order allocation platform according to an embodiment of the present invention;
fig. 8 is a schematic hardware structure diagram of an order distribution system of an order distribution platform according to an embodiment of the present invention.
Detailed Description
In order to make the technical problems, technical solutions and advantageous effects to be solved by the present application clearer, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of and not restrictive on the broad application.
The embodiment of the application provides an order distribution method which is applied to computer equipment. When the order distribution method is implemented, the order distribution method is configured on a computer device in the form of an object script, and the computer device executes the object script to further execute the steps of the order distribution method provided by the embodiment. The execution subject is a target server in the server cluster for distributing the order. Here, the server cluster may be a server cluster composed of a plurality of servers, on the basis of which the distributed order distribution system is built, so that each component required for building the distributed order distribution system can be configured into each server in the server cluster, and the server configured with the distributed order distribution system component may also be referred to as a component server. Data sharing or data synchronization can be performed between the servers in the server cluster. On this basis, an object script file is configured to any server in the server cluster, and the object script file describes the order allocation method provided by this embodiment, so that the server configured with the object script file can execute each step in the order allocation method by executing the object script file. Or, configuring a new server for the server cluster, configuring a target script file for the new server, and describing the order allocation method provided by this embodiment by the target script file, so that the new server can execute each step in order allocation by executing the target script file.
When the order distribution is realized, a target server used for distributing the order in the server cluster receives order information uploaded by a user through a terminal, wherein the order information comprises user grade and reservation address information. And acquiring the grade information of all the operators, and screening out a first operator set with the grade information matched with the user grade. And acquiring real-time position information of each salesman in a first salesman set, and screening out a second salesman set with the real-time position information matched with the reservation address information from the first salesman set. And performing priority ordering on all the operators in the second operator set based on a preset rule. And distributing the order information to a task list of a target operator, wherein the target operator is the operator with the highest priority order so as to ensure that the order can be processed in time. The order distribution scheme increases the diversity of order distribution modes, and has high flexibility and good user experience.
Referring to fig. 1, fig. 1 is a flowchart illustrating a first implementation of an order allocation method provided in an embodiment of the present application. The order distribution method comprises the following steps:
s10: and receiving order information uploaded by a user through a terminal, wherein the order information comprises user grade and reservation address information.
In step S10, the order information is order information included in an electronic order that the user needs to request the insurance agency to distribute the employee to transact the business at home, and the employee transacts the business by sending the business transaction request through the insurance agency APP or the insurance agency client. The order information comprises the name, sex, age, mobile phone number, transacted business type, user grade, reservation address information and the like of the user. The user fills in the information on the electronic order and uploads the order information on the client, and the server receives the order information uploaded by the user.
S20: and acquiring the grade information of all the operators, and screening out a first operator set with the grade information matched with the user grade.
S30: and acquiring real-time position information of each salesman in a first salesman set, and screening out a second salesman set with the real-time position information matched with the reservation address information from the first salesman set.
In step S30, the real-time location information of each service person may be acquired as satellite positioning information uploaded by the service person in real time on the order distribution system, or as real-time location information manually filled in by voice input. In addition, the real-time position information corresponding to each operator in the operator information set can be obtained, and the real-time position information can also be determined jointly based on the first position information of the electronic order currently processed by each operator and/or the second position information of the electronic order to be processed next.
The user submits the reservation address information through the terminal, the real-time position information of the salesman also needs to be collected to the order distribution system, and the server compares the obtained real-time position information with the reservation address information. The real-time location information of the attendant is compared to the subscription address information to specify a minimum unit, such as a street. And if the real-time position information is matched with the reservation address information, listing the salesman information into a first salesman list.
When the GPS positioning information uploaded by the service staff cannot be used for determining the real-time position information of each service staff, or the GPS positioning information uploaded by the service staff is not received, the real-time position information of each service staff may be determined together based on the first position information of the electronic order currently being processed by each service staff and/or the second position information of the electronic order to be processed next. Uploading of GPS location information becomes difficult when the network state is poor, and the order information is processed according to the order information of the order of the wait-to-process and the pending electronic order of the wait-to-process of the wait person, which is determined by the order distribution system, for example, there is the wait-to-process and the pending order information in the task list of the wait person, because the wait person processes the order information according to the order of the order information in the task list, the real-time location information of the wait person may be the address located on the order being processed, may be the address located on the order information to be processed, and may be the path between the order being processed and the address of the order to be processed. Real-time location information corresponding to each attendant can be determined based on the electronic first location information being processed by each attendant and/or the second location information of the electronic order to be processed next.
S40: and performing priority ordering on all the operators in the second operator set based on a preset rule.
S50: and distributing the order information to a task list of a target operator, wherein the target operator is the operator with the highest priority order.
Referring to fig. 2, fig. 2 is a flowchart illustrating a second implementation of the order allocation method according to the embodiment of the present application. The order distribution method comprises the following steps:
s10: and receiving order information uploaded by a user through a terminal, wherein the order information comprises user grade and reservation address information.
S21: and acquiring the service information of the service staff.
In step S21, the service information includes customer information, historical policy transaction records, appointment time, appointment location, and the like.
S22: and determining a corresponding service type according to the service information, inputting the service type into a preset operator matching model for matching, and obtaining grade information matched with the service information.
In step S22, a label set of the current salesman who is connected to the customer and purchases the product is extracted from the business information, a business type corresponding to the business information is determined by the label set, and the business type is input into a preset salesman matching model to match the salesman class required by the current salesman. For example, the current service information has labels that the gender of the customer is female, the age of 23 years, the car insurance is purchased, the family income is high, the number of family insurance purchasers is 1.8, and the like, if the grade of the current service information obtained through the labels is A, and the historical service shows that the grade required by the service staff connected with the customer needs to be between a and b, the service staff with the grade between a and b is preliminarily screened
S23: and screening out a first salesman set of which the grade information is matched with the grade of the user.
In step S23, the salesman whose level information matches the user level is screened out to obtain a first salesman set.
S30: and acquiring real-time position information of each salesman in a first salesman set, and screening out a second salesman set with the real-time position information matched with the reservation address information from the first salesman set.
S40: and performing priority ordering on all the operators in the second operator set based on a preset rule.
S50: and distributing the order information to a task list of a target salesman, wherein the target salesman is the salesman with the highest priority ranking.
Referring to fig. 3, fig. 3 is a flowchart illustrating a third implementation of the order allocation method according to the embodiment of the present application. The order distribution method comprises the following steps:
s10: and receiving order information uploaded by a user through a terminal, wherein the order information comprises user grade and reservation address information.
S21: and acquiring the service information of the service staff.
S22: and determining a corresponding service type according to the service information, inputting the service type into a preset operator matching model for matching, and obtaining grade information matched with the service information.
S23: and screening out a first salesman set of which the grade information is matched with the grade of the user.
S30: and acquiring real-time position information of each salesman in a first salesman set, and screening out a second salesman set with the real-time position information matched with the reservation address information from the first salesman set.
S41: and all the service data in the latest preset time range are acquired regularly, the acquired service data are input into a preset data statistical analysis system for statistical analysis, and the statistical analysis obtains the numerical value of each preset performance index of each salesman.
In step S41, all the service data in the latest preset time range (for example, in the latest one month) are obtained regularly, the service data includes service transaction records (including new service transaction records and renewal transaction records), due service information, and the like, and each service data includes information such as name or number of the waiter, and the service amount. The electronic device is provided with a preset data statistical analysis system, all acquired business data are input into the data statistical analysis system by the electronic device, all business data related to each salesman can be found out from the acquired business data by the data statistical analysis system respectively, and then statistics and calculation of each preset performance index are carried out on the business data related to each salesman, so that the numerical value of each preset performance index of each salesman is obtained, wherein the preset performance indexes comprise a policy insurance premium, a renewal rate, an activity rate and the like.
S42: and calculating the obtained numerical value of each preset performance index of each salesman according to a preset score calculation rule to obtain the total performance score of each salesman.
The preset scoring calculation rule may be a weighted sum of the numerical values of the preset performance indicators according to preset weights.
S43: and the various salesmen are prioritized according to the total performance score from high to low.
S50: and distributing the order information to a task list of a target operator, wherein the target operator is the operator with the highest priority order.
In one embodiment, as shown in fig. 4, the step S30 specifically includes the following steps:
s31: and gridding and dividing the urban area according to population density distribution to obtain a plurality of grid areas.
Specifically, the gridding division is based on large scale data of a target urban area, and different unit gridding divisions are formed by transverse aggregation or longitudinal decomposition according to a certain proportion in space according to population density distribution in the target urban area. Because there are many orders to be processed corresponding to densely populated areas, the target city area needs to be divided into gridding partitions, which is convenient for business personnel to process the gridding partitioned orders in a centralized manner. The target urban area is divided, wherein the target urban area is not limited to a size range, and is divided according to needs and specific conditions, but the urban area is generally divided by taking a city as a unit. Because population distribution in urban areas is usually uneven, the urban areas are subjected to meshing division according to proportion according to population density distribution in the urban areas, and the target urban areas are subjected to meshing division to obtain meshing division.
S32: and taking the grid area where the reservation address information is located as a center, and if the real-time position information is located in 8 grid areas surrounding the center, matching the real-time position information with the reservation address information, wherein the central grid area and the 8 grid areas surrounding the center are distributed according to a Sudoku.
In one embodiment, as shown in fig. 5, the step S30 specifically includes the following steps:
s33: and drawing a thermodynamic diagram according to the historical order position information of the target city area.
S34: and gridding and dividing the thermodynamic diagram according to a preset proportion strategy to obtain a plurality of grid areas.
Specifically, the thermodynamic diagram is visual data of the area, and the thermodynamic diagram is drawn according to the distribution condition of the historical order position information of the target city area in the target city area, namely the thermodynamic diagram for rendering the historical order position density is generated according to the longitude and latitude corresponding to the historical order position and the map of the target city area. Finally, the thermodynamic diagram is subjected to gridding division to obtain a gridding address division area. According to the preset proportion strategy, the proportion of grids used for dividing the position with high density of the geographic position of the historical order, namely the position with deep color in the thermodynamic diagram is smaller, and the grids with low density of the historical order position and high use proportion in the thermodynamic diagram are divided. The grid division not only divides the target city area according to the historical order position information, but also divides the target city area according to the density of the historical order positions to obtain a grid address division area. The historical order position information can represent population density distribution, corresponding operators are configured for each grid address division area, and the operator information sets are approximately equal, so that the number of orders processed by the operators in each grid address division area is balanced, and the condition that different operators do not saturate or saturate excessively is avoided.
S35: and taking the grid area where the reservation address information is located as a center, and if the real-time position information is located in 8 grid areas surrounding the center, matching the real-time position information with the reservation address information, wherein the central grid area and the 8 grid areas surrounding the center are distributed according to a Sudoku.
In one embodiment, the step S30 specifically includes the following steps:
s36: and if the path distance between the real-time position information and the reservation address information is smaller than or equal to a preset distance, matching the real-time position information with the reservation address information.
Wherein the preset distance can be 5-10 km.
In the above method embodiment, an embodiment of the present invention further provides an order distribution platform, as shown in fig. 6, the platform 10 may include the following modules:
the receiving module 11 is configured to receive order information uploaded by a user through a terminal, where the order information includes a user level and reservation address information;
the first screening module 12 is configured to acquire the level information of all the operators, and screen out a first operator set in which the level information matches with the user level;
the second screening module 13 is configured to acquire real-time location information of each salesman in a first salesman set, and screen a second salesman set from the first salesman set, where the real-time location information matches the reservation address information;
a priority ranking module 14, configured to perform priority ranking on all the employees in the second employee set based on a preset rule;
and the allocating module 15 is configured to allocate the order information to a task list of a target salesman, where the target salesman is a salesman with the highest priority ranking.
It should be understood that, in the functional module diagram of the order distribution platform shown in fig. 6, each module is used to execute each step in the embodiment corresponding to fig. 1 to 6, while each step in the embodiment corresponding to fig. 1 to 5 has been explained in detail in the above embodiment, and please refer to the relevant description in the embodiment corresponding to fig. 1 to 5 specifically, which is not repeated herein.
Another embodiment of the present invention provides an order distribution platform, as shown in fig. 7, the order distribution platform 10 includes:
one or more processors 110 and a memory 120, where one processor 110 is illustrated in fig. 7, the processor 110 and the memory 120 may be connected by a bus or other means, and where fig. 7 illustrates a bus connection.
The memory 120 may include a program storage area and a data storage area, wherein the program storage area may store an application program required for operating the platform and at least one function. The storage data area may store data created according to the use of the platform 10, and the like. Further, the memory 120 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, memory 120 optionally includes memory located remotely from processor 110, which may be connected to platform 10 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
One or more units are stored in the memory 120, which when executed by the one or more processors 110, perform the order allocation method in any of the method embodiments described above, e.g., performing the method steps S100-S400 of fig. 1 described above.
Another embodiment of the present invention further provides an order distribution system, as shown in fig. 8, the system includes several clients 20, a server 30, and the order distribution platform 10 as described above. The plurality of clients 20 and the server 30 are in communication connection with the order distribution platform 10, wherein the plurality of clients 20 are used for various dealers to log in the order distribution platform 10 and fill in bulletin information acquisition requests, and the server 30 is used for storing bulletin information.
Embodiments of the present invention provide a non-transitory computer-readable storage medium having stored thereon computer-executable instructions for execution by one or more processors, e.g., to perform the method steps described above in fig. 1-5.
By way of example, non-volatile storage media can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), electrically erasable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM), which acts as external cache memory. By way of illustration and not limitation, RAM is available in many forms such as Synchronous RAM (SRAM), dynamic RAM, (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The disclosed memory components or memory of the operating environment described herein are intended to comprise one or more of these and/or any other suitable types of memory.
Of course, it will be understood by those skilled in the art that all or part of the processes of the methods of the above embodiments may be implemented by instructing relevant hardware (such as a processor, a controller, etc.) through a computer program, which may be stored in a non-volatile computer-readable storage medium, and the computer program may include the processes of the above method embodiments when executed. The storage medium may be a memory, a magnetic disk, a floppy disk, a flash memory, an optical memory, etc.
It should be understood that the above-mentioned embodiments are only used to illustrate the technical solutions of the present invention, and not to limit the same. Although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: modifications of the technical solutions described in the embodiments or equivalent replacements of some technical features may still be made. Such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (10)
1. An order allocation method, comprising:
receiving order information uploaded by a user through a terminal, wherein the order information comprises user grade and reservation address information;
acquiring grade information of all the operators, and screening out a first operator set with the grade information matched with the user grade;
acquiring real-time position information of each salesman in a first salesman set, and screening out a second salesman set with the real-time position information matched with the reservation address information from the first salesman set;
all the salesmen in the second salesmen set are subjected to priority sequencing based on a preset rule;
and distributing the order information to a task list of a target operator, wherein the target operator is the operator with the highest priority order.
2. The method of claim 1, wherein the obtaining of the ranking information of all the operators comprises:
acquiring service information of a waiter;
and determining a corresponding service type according to the service information, inputting the service type into a preset salesman matching model for matching, and obtaining grade information matched with the service information.
3. The method of claim 1, wherein the screening out a second set of operators from the first set of operators that match the real-time location information with the subscription address information comprises:
carrying out gridding division on the urban area according to population density distribution to obtain a plurality of grid areas;
and taking the grid area where the reservation address information is located as a center, and if the real-time position information is located in 8 grid areas surrounding the center, matching the real-time position information with the reservation address information, wherein the central grid area and the 8 grid areas surrounding the center are distributed according to a Sudoku.
4. The method of claim 1, wherein the screening out a second set of operators from the first set of operators that match the real-time location information with the subscription address information comprises:
drawing a thermodynamic diagram according to historical order position information of the target city area;
carrying out gridding division on the thermodynamic diagram according to a preset proportion strategy to obtain a plurality of grid areas;
taking the grid area where the reservation address information is located as a center, and if the real-time position information is located in 8 grid areas surrounding the center, matching the real-time position information with the reservation address information, wherein the grid area of the center and the 8 grid areas surrounding the center are distributed according to a nine-square grid.
5. The method of claim 1, wherein the screening out a second set of operators from the first set of operators that match the real-time location information with the subscription address information comprises:
and if the path distance between the real-time position information and the reservation address information is smaller than or equal to a preset distance, matching the real-time position information with the reservation address information.
6. The method of claim 1, wherein the prioritizing all of the second set of clerks based on a preset rule comprises,
all the service data in the latest preset time range are obtained regularly, the obtained service data are input into a preset data statistical analysis system for statistical analysis, and the numerical values of all the preset performance indexes of each salesman are obtained through statistical analysis;
calculating the obtained numerical value of each preset performance index of each salesman according to a preset score calculation rule to obtain the total performance score of each salesman;
and the various salesmen are prioritized according to the total performance score from high to low.
7. An order distribution platform, comprising:
the receiving module is used for receiving order information uploaded by a user through a terminal, and the order information comprises user grade and reservation address information;
the first screening module is used for acquiring the grade information of all the salesmen and screening out a first salesmen set of which the grade information is matched with the user grade;
the second screening module is used for acquiring real-time position information of each salesman in the first salesman set and screening out a second salesman set with the real-time position information matched with the reservation address information from the first salesman set;
the priority ordering module is used for carrying out priority ordering on all the salesmen in the second salesmen set based on a preset rule;
and the distribution module is used for distributing the order information to a task list of a target operator, wherein the target operator is the operator with the highest priority order.
8. An order distribution platform comprising at least one processor; and (c) a second step of,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the order allocation method of any of claims 1-6.
9. An order distribution system comprising a plurality of clients, a server and an order distribution platform according to claim 8; and the plurality of clients and the server are in communication connection with the platform.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 6.
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| CN202210761999.6A CN114971412A (en) | 2022-06-29 | 2022-06-29 | Order distribution method, order distribution platform, order distribution system and storage medium |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116757893A (en) * | 2023-04-10 | 2023-09-15 | 南京勤力信息科技有限公司 | Cross-regional enterprise government service intelligent matching method and Internet platform system |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116757893A (en) * | 2023-04-10 | 2023-09-15 | 南京勤力信息科技有限公司 | Cross-regional enterprise government service intelligent matching method and Internet platform system |
| CN116757893B (en) * | 2023-04-10 | 2024-03-05 | 南京勤力信息科技有限公司 | Cross-regional enterprise government service intelligent matching method and internet platform system |
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